Enterprise Thought Leadership

Tim Bond speaks with Carson Hostetter , who leads RingCentral's AI and customer experience strategy, about how voice technology is reshaping business operations from call centres to reception desks. RingCentral handles billions of minutes of voice annually across 500,000 customers globally. Their AI receptionist product launched in June 2024 and already serves over 3,000 customers, demonstrating strong market appetite for automated voice solutions.The conversation explores two critical benefits. First, voice agents handle customer interactions naturally, without forcing callers through menu trees. Second, every interaction generates transcripts that reveal customer sentiment, sales opportunities, service gaps and product development insights. Carson explains why RingCentral partners with multiple AI providers including OpenAI, Google and AWS, maintaining an open platform rather than building proprietary models. The discussion covers implementation, from five-minute setup for small businesses to complex enterprise integration, and examines how AI enables market expansion rather than just cost reduction.Topics covered• Traditional IVR limitations versus natural language voice agents.• Setting up AI receptionists in under five minutes with minimal configuration.• Transcript analysis for sentiment tracking, opportunity identification and business intelligence.• Open platform strategy with multiple AI providers versus proprietary models.• Performance benchmarks and customer adoption rates since June 2024 launch.• Use cases spanning reception, technical support and complex customer service.• Future work patterns and the optimistic case for AI augmentation.• Moving from defensive cost-cutting to offensive market expansion strategies.• How small businesses and enterprises apply the technology differently.Timestamps00:00:00 Introduction and AI's competitive impact00:05:23 RingCentral overview and market position00:09:00 Evolution from ChatGPT moment to voice agents00:15:17 Market readiness for AI solutions00:17:50 Why voice AI is easier than traditional IVR systems00:20:00 The data opportunity from call transcripts00:25:27 Performance benchmarks and customer growth metrics00:27:31 Use cases from reception to complex support scenarios00:30:21 Why "AI receptionist" undersells the platform capability00:32:31 Future patterns of work and employment outlook00:36:22 Why choose RingCentral and how to get startedGuest bioCarson Hostetter leads RingCentral's AI and customer experience strategy, bringing 26 years of communications industry experience. Starting with Nortel Networks in 1999, he joined RingCentral in 2016 to build and scale the company's enterprise business. After serving as Chief Revenue Officer for three and a half years, Carson now focuses on developing RingCentral's next generation of AI-infused communication solutions, ensuring practical customer outcomes whilst maintaining the company's open platform philosophy across partnerships with major AI providers.• • • Related episodesBrowse previous episodes exploring AI implementation and business transformation at TechPros.io.Follow the Enterprise Thought Leadership Podcast on Apple and Spotify to never miss an episode. Leave a rating to help others discover these conversations. Share your burning questions or topic suggestions by emailing podcasts@techpros.io.Join the growing podcast community on LinkedIn.Explore upcoming TechPros.io roundtables and virtual experiences.

80% of software companies are zombies. After three decades guiding thousands of software founders through exits and acquisitions, Mark Edwards reveals the uncomfortable truth: most businesses exist in endless loops, neither thriving nor dying. In this episode, Mark shares what separates the 20% who succeed from the zombie majority. His verdict? Strategy beats everything else. The conversation explores how AI quadruples the number of software companies whilst collapsing barriers to entry. Mark warns that despite new technology, success still demands emotional intelligence, strategic positioning, and teams that balance technical, creative and commercial capabilities.Guest bioMark Edwards brings three decades of experience in software company mergers and acquisitions. As founder of Boss Equity (established 1999), he has worked with thousands of software companies across document management, workflow automation and enterprise solutions. His pattern-matching across hundreds of exits reveals why most software businesses fail to escape mediocrity. Mark combines his early creative background in photography with deep commercial expertise to help founders understand strategic positioning and market dynamics.Topics covered• Why 80% of software companies exist as zombie businesses. • The three-word answer to escaping mediocrity: strategy, strategy, strategy. • Only 35% of companies actually know their competition. • Less than 5% seeking investment successfully secure funding. • How AI quadruples the number of software companies in five years. • Why emotional connection, not features, drives B2B sales decisions. • The danger of technical founders building companies in their own image. • Barriers to entry collapsing through tools like Lovable. • The need for cerebral diversity: creatives, strategists and technicians. • CEOs as figureheads who make their teams look exceptional.Timestamps00:00:00 Mark's lifelong obsession with improvement 00:03:14 Building Boss Equity and international expansion 00:05:00 Pattern matching across thousands of companies 00:08:10 The 80% zombie company problem explained 00:10:00 Strategy as the only escape route 00:11:13 Understanding real competition and market positioning 00:16:00 Marketing failures and disconnected sales processes 00:18:17 Zombie loops and endless investment searches 00:19:48 Why less than 5% achieve institutional investment 00:22:32 AI creating the most exciting time in software 00:26:00 Barriers collapsing and competition intensifying 00:29:23 The rise of peer-to-peer funding models 00:32:00 Companies reaching hundreds of millions overnight 00:37:11 The need for cerebral diversity in teams 00:39:30 CEOs as figureheads who elevate their teams 00:41:05 The future of RPA and business operating systems 00:47:38 Psychology as the key to successful dealsResources and links• Mark Edwards on LinkedIn • Tim Bond on LinkedIn • Outsmart Strategy  • Boss Equity – Mark's M&A advisory firm • Lovable.com – No-code platform changing barriers to entry • FREE AI Acceleration ReportListen now• Apple Podcasts• SpotifyRelated episodes• Episode 74: Marketing in an AI-first world • Episode 72: Building scalable software businessesGet your AI acceleration reportWant to teach your team to build their own AI agents that act like teammates, boosting productivity, quality, and job satisfaction? Get your FREE AI Acceleration Report (for listeners with teams of six or more), a quick team survey and consultation that maps priority workflows, time saved and ROI from an AI upskilling programme. Visit Cogniscale.com and enter promo code PODCAST.Connect with usFollow Enterprise Thought Leadership for weekly episodes exploring technology, operations and the future of work. Rate and review this episode if you found it valuable. Have burning questions or topics for future episodes? Email podcasts@techpros.io• TechPros.io• Upcoming Events• ⁠LinkedIn Community⁠

The Financial Times has achieved 44% productivity gains in certain areas whilst maintaining their commitment never to replace journalists with AI. McKinley Hayden, who leads data value and strategy at the FT, reveals how they won Gen AI Initiative of the Year by focusing on values before technology. With over 2,000 active weekly users across their 3,500-strong workforce, the FT has built an implementation programme that measures emotions alongside capabilities, creating a network of departmental AI representatives who serve as two-way conduits for change. McKinley explains why simplicity matters when "the target is not fixed" and shares surprising examples where AI actually added time rather than saving it.Topics covered • How values and responsibility drive effective AI adoption at scale • Building voluntary participation programmes that achieve 57% workforce engagement • Why measuring emotions matters as much as measuring capabilities • Creating AI playbooks for common tasks across all departments • Where AI fails: when augmentation adds time instead of saving it • Navigating constant change when implementation targets keep moving • The power of departmental representatives as change agents • Balancing quick wins with long-term transformation goalsTimestamps 00:01:44 – McKinley's role in data value and strategy at the FT 00:03:03 – The Financial Times' global presence and reach 00:04:10 – Winning Gen AI Initiative of the Year award 00:05:41 – Values-driven approach: why principles come first 00:10:47 – Thoughtful and responsible AI adoption strategies 00:13:55 – Results assessment: achieving 44% efficiency gains 00:17:29 – Survey methodology: measuring emotions and capabilities 00:22:25 – New CEO's focus on AI outcomes and priorities 00:24:17 – AI implementation programme structure and teams 00:27:29 – Complex AI versus simple augmentation approaches 00:31:56 – Demonstrating value to leadership and stakeholders 00:34:09 – Why the implementation target isn't fixedGuest bio McKinley Hayden leads data value and strategy at the Financial Times, where she has spearheaded the organisation's award-winning approach to AI implementation. Her work focuses on balancing technological innovation with the FT's core values of human-powered journalism. Under her leadership, the FT's AI programme has achieved significant adoption rates and productivity gains whilst maintaining a thoughtful, values-first approach. McKinley brings expertise in change management, data strategy, and organisational transformation to help traditional media organisations navigate digital evolution.Resources and links • Tim Bond on LinkedIn – podcast host and enterprise technology leader: https://www.linkedin.com/in/tngbond/ • McKinley Hayden on LinkedIn: https://www.linkedin.com/in/mckinleyhyden/• Financial Times website: https://www.ft.com • TechPros.io: https://techpros.io/ • Upcoming events and roundtables: https://techpros.io/virtual-experiences/ • Enterprise Thought Leadership community on LinkedIn: https://www.linkedin.com/company/enterprise-thought-leadership/Related episodes • Episode 73: AI transformation in publishing • Episode 69: Building data-driven cultures • Episode 65: Change management in traditional industriesCalls to action Follow Enterprise Thought Leadership on Spotify Rate this episode on Apple PodcastsJoin the conversation in our LinkedIn community Share your AI implementation challenges: podcasts@techpros.ioWant to teach your team to build their own AI agents that act like teammates, boosting productivity, quality, and job satisfaction? Get your FREE AI Acceleration Report (for listeners with teams of six or more), a quick team survey and consultation that maps priority workflows, time saved and ROI from an AI upskilling program. Visit Cogniscale.com and enter promo code PODCAST details in the show notes.

A third of marketing teams struggle to extract real value from generic AI tools. Maria Liw, Global Head of Marketing at SimCorp, explains how structured AI training converted sceptical team members into confident practitioners, achieving 2-3x productivity gains whilst maintaining quality standards.SimCorp serves financial institutions managing over $40 trillion in assets, with a marketing organisation of 30 to 40 people spanning global content, regional campaigns, events and brand. As CogniScale's first client, they pioneered a systematic upskilling approach rather than casual experimentation. The results sound almost unbelievable: 92% time reductions on industry interview writeups, 1100% productivity gains on specific tasks, and an overall 2-3x productivity increase across the team.The conversation explores what changed when SimCorp moved from giving teams AI tools to experiment with, to designing structured training where participants worked on real projects during workshops. Maria shares how initial scepticism quickly transformed as team members experienced quality outputs and discovered AI could serve as a strategic thinking partner, not just a production tool.Topics covered• Why generic AI tools weren't delivering marketing value for SimCorp's team.• Designing a pilot programme around real workflows and deadlines.• The importance of slowing down initially to set up AI projects properly.• Converting team scepticism into genuine enthusiasm through hands-on results.• Using AI as a strategic partner and sounding board, not just a production tool.• Building collaboration infrastructure as more teams adopt AI.• Security, legal and compliance considerations when scaling AI adoption.Advice for marketing leaders starting their AI transformation journey.Timestamps2:33 - Maria's background and SimCorp's marketing organisation06:38 - How Maria and Tim's collaboration began09:03 - Framing the pilot as a learning opportunity11:12 - Workshop experiences and hands-on learning13:43 - Participant reactions before and after training16:13 - Change management and team enthusiasm18:20 - Results: astronomical numbers that feel unrealistic21:10 - Stress relief and strategic thinking benefits23:16 - The importance of slowing down to move fast25:30 - Competitive advantage and future collaboration28:22 - Security, legal and compliance considerations29:56 - Advice for marketing leaders on AI adoptionGuest BioMaria Liw is Global Head of Marketing at SimCorp, a leader in investment management technology serving financial institutions that collectively manage over $40 trillion in assets. With over 30 years of experience in the FinTech industry spanning both buy and sell sides, Maria has held roles across all marketing disciplines. Most recently, she headed global digital and content before becoming head of marketing. Maria brings a unique perspective to AI adoption, having led SimCorp's marketing team through a structured transformation from AI experimentation to systematic capability building.Resources and links• Maria Liw on LinkedIn• Tim Bond on LinkedIn • SimCorp • CogniScale (AI training) • Free AI acceleration report • TechPros.io • Upcoming Events and Roundtables• Podcast community on LinkedInListen and subscribe on Apple PodcastsListen and follow on SpotifyJoin our podcast community on LinkedInRate and review the podcast on your platform to help other listeners discover the show.Want to teach your team to build their own AI agents that act like teammates, boosting productivity, quality and job satisfaction? Get your free AI acceleration report (for listeners with teams of six or more), a quick team survey and consultation that maps priority workflows, time saved and ROI from an AI upskilling programme. Visit cogniscale.com/ai-acceleration-report and enter promo code PODCAST.Have burning topics or questions for the podcast? Email podcasts@techpros.ioFind out more about TechPros.io

"Agents are like enthusiastic employees who don't have a conscience and aren't afraid of getting fired." This stark warning from Oren Michels, CEO of Barndoor.ai, captures why enterprises desperately need governance for their AI workforce. With documented cases of ungoverned agents accidentally deleting entire code bases, the stakes couldn't be higher.Drawing from his experience founding Mashery (acquired by Intel), Oren recognised that AI agents face the same governance challenges as APIs did 15 years ago – but with far greater risks. He reveals why Anthropic's MCP protocol lacks built-in security, explains the four critical vectors of agent security, and shares why Moderna's HR department is leading their AI agent strategy. For any organisation deploying AI agents, Oren's insights on treating them as digital employees rather than traditional software could mean the difference between transformation and catastrophe.Guest bioOren Michels is CEO and co-founder of Barndoor.ai, pioneering security and governance for AI agents. Previously, he founded Mashery, an API management company acquired by Intel, where he served as GM of Intel's API Management Group. His experience scaling API governance to hundreds of enterprise customers now informs his approach to securing the next generation of digital workers.Topics covered• Understanding MCP and why agents need different protocols than traditional software• The four vectors of agent security: agent identity, human identity, tool access, and tasks• Why agents are "enthusiastic employees without a conscience"• HR and IT collaboration to manage agents as digital employees• Building platforms showing which humans achieve value from agents• Documented failures: ungoverned agents deleting entire code bases• Moderna's HR-led approach to AI agent deployment• Evolution from internal use to cross-company agentic workflows• Future implications for early career professionalsKey timestamps00:00:00 – Introduction to securing AI agents00:02:13 – Why API management patterns apply to AI agents 00:07:15 – MCP protocol and its security gaps00:12:14 – What Barndoor does00:20:06 – Documented failures and ungoverned agents00:23:39 – Moderna's HR-led approach00:26:09 – HRIS for the agent workforce00:34:43 – Future of work and early career challengesResources mentioned• Oren Michels on LinkedIn – CEO of Barndoor.ai • Tim Bond on LinkedIn – Podcast host • Barndoor.ai – AI agent security platform • Intel – Acquired MasheryListen and subscribeFound this valuable? Subscribe on: Spotify | Apple PodcastsJoin our LinkedIn community for ongoing discussionsQuestions? Email: podcasts@techpros.io Learn more: https://techpros.io/Full transcript available below.

A third of CMOs report little to no AI implementation in their organisations. Chris Daly's verdict? "You're gonna be history." In this episode, the CEO of the Chartered Institute of Marketing shares why marketing professionals must rapidly adapt or risk obsolescence. Drawing from his military background and leadership of this 113-year-old institution, Chris reveals how marketing can finally shed its "pens and t-shirts department" reputation to become the engine of business growth. We explore the critical balance between AI adoption and human creativity, examine WPP's 50% devaluation as a cautionary tale, and discover why some agencies now revise their AI policies every three months just to keep pace.Topics covered• Marketing's evolution from sales offshoot to business growth function.• Why professional standards matter more than ever in the AI era.• Four principles for ethical AI implementation in marketing.• The hidden dangers of shadow AI when employees use personal licences.• How bias in AI systems can damage customer relationships.• WPP's challenges and what they signal for traditional agencies.• Why CIM is considering traditional exams again, as AI can too easily complete assignments.• The Global Professional Marketing Framework with 207 competency aspects.• How treating AI as a colleague rather than a barrier preserves customer connection.• Why continuous learning is the only survival strategy for marketers.Timestamps00:00:34 CIM's 113-year journey from sales to chartered status00:02:44 From military values to marketing leadership00:05:29 Professional qualifications: university to C-suite journey00:14:00 The AI changes in marketing education00:17:35 Four principles for ethical AI: integrity, quality, transparency, awareness00:21:00 Breaking free from the "pens and t-shirts department" perception00:26:00 Five brand risks of generative AI adoption00:29:55 Shadow AI: when employees go rogue with personal licences00:33:41 Global Professional Marketing Framework for organisations00:37:16 WPP's value loss and agency changes00:41:14 One habit every marketer needs: staying currentGuest bioChris Daly is CEO of the Chartered Institute of Marketing, the world's largest professional body for marketing with over 30,000 members globally. A former military officer, Chris brings principles of trust, ethics and professionalism from his service background to marketing leadership. He champions marketing as a business growth function and leads CIM's mission to professionalise an industry navigating AI changes.Resources mentioned• Chartered Institute of Marketing - newly redesigned website with qualifications, training and frameworks• Chris Daly on LinkedIn• Tim Bond on LinkedIn• Gartner CMO research February 2024 study on AI adoption• EU AI Act passed March 2024• WPP investor information context on recent valuation changes• IBM partnership for AI training (via CIM website)• Global Professional Marketing Framework launching November 2024 at World Marketing Forum• CIM's four principles for ethical AI use in marketing• Marketing Cloud, CIM's bridge programme between university and first careerRelated episodes• Episode 68: AI changes in enterprise marketing• Episode 71: Building ethical frameworks for business AI adoptionSubscribe and connectEnjoyed this discussion? Follow Enterprise Thought Leadership on Spotify and Apple Podcasts for weekly conversations with business and technology leaders.Rate and review the podcast to help others find these insights. Join our LinkedIn community at Enterprise Thought Leadership for ongoing discussions.Questions for future episodes? Email podcasts@techpros.ioTranscriptA full transcript of this episode is available below for accessibility and reference.This episode was recorded in July 2024. AI developments and statistics may have evolved since recording.

Tim Bond speaks with Rich Waldron, CEO of Tray.ai, who since 2012 has been building the infrastructure that allows AI agents to truly operate within enterprises. Rich explains the difference between AI's reasoning capabilities (the brain) and its ability to take action across systems (the body), and why this distinction matters for organisations implementing agentic technologies.The conversation explores why 60% of early AI projects fail, the importance of specialised agents over "everything agents", and how companies can avoid common pitfalls. Rich shares insights from over a decade of connecting 800+ applications and databases, revealing what separates successful implementations from costly failures.Key topics covered:• Understanding the body and brain concept in AI agents• Why specialised agents outperform generalised ones• Design principles for avoiding hallucinations• Building cross-functional teams for AI success• The shift from traditional software to constantly evolving agents• The opportunities for young professionals to build our agentic future Timestamps:00:00:00 Introduction to agentic workflows 00:01:49 Rich's journey from university to founding Tray.ai 00:05:38 Early recognition of AI's potential 00:07:48 What is an integration platform as a service (IPaaS)? 00:11:31 The body and brain concept explained 00:14:39 Tools vs knowledge in agent design 00:19:21 Over 800 connectors and growing 00:22:15 Human-in-the-loop considerations 00:25:01 Addressing hallucinations in business processes 00:31:00 Getting started with agentic implementation 00:38:00 Growth strategy and market approach 00:42:47 Competitive advantages and future outlook 00:45:11 Advice for young professionals entering the workforceWant to learn more? Visit Tray.ai's website: https://tray.ai  Connect with Rich Waldron on LinkedIn: https://www.linkedin.com/in/richwaldron/  Connect with Tim Bond: https://www.linkedin.com/in/tngbond/ If you like our podcast, please do follow us and rate each episode. Do you have burning topics or questions you'd like us to explore on the podcast? Email our team at podcasts@techpros.ioFind out more about TechPros.io: https://techpros.io/ Upcoming Events and Roundtables: https://techpros.io/virtual-experiences/ Join our budding podcast community on LinkedIn: https://www.linkedin.com/company/enterprise-thought-leadership/

Bryan Murphy, CEO of Smartling, shares how his company evolved from a software-focused translation provider into an AI-enhanced platform that delivers eight times more content for the same budget. Having joined just before ChatGPT's launch, Bryan led a product overhaul achieving 64% revenue growth whilst quadrupling translator productivity.The conversation explores Smartling's journey from neural machine translation to multi-layered AI workflows that solve quality, fluency, and cultural adaptation challenges. Bryan explains their multi-model approach, automated quality assurance systems, and how they help companies like IHG Hotels, British Airways, and IBM translate content at scale.Bryan also reveals why implementing AI across internal operations proved more challenging than the product changes themselves. He shares specific examples from leading company-wide change, the importance of dedicated resources, and why CEOs must be prepared for their initial AI plans to fail and require iteration.Timestamps:01:58 Bryan's background and eBay Motors experience02:24 Joining Smartling and the ChatGPT moment03:18 Company's tech-forward foundation04:02 From neural machine translation to AI translation07:04 Current product architecture and workflow09:22 Multi-model approach and benchmarking11:28 4× productivity gains for translators13:04 8× content for same budget achievement14:58 Customer case studies and industries served16:35 Internal AI challenges across departments19:05 Sales team doubles productivity20:42 Build vs buy debate and last mile complexity25:47 Customer journey and onboarding process28:22 Action steps for enterprise leadersWant to learn more?Visit Smartling website: https://www.smartling.com/ Connect with Bryan Murphy on LinkedIn: https://www.linkedin.com/in/bryanmurphy2/ Connect with Tim Bond: https://www.linkedin.com/in/tngbond/ Email tim.b@techpros.ioIf you like our podcast, please do follow us and rate each episode. Do you have burning topics or questions you'd like us to explore on the podcast? Email our team at podcasts@techpros.ioFind out more about TechPros.io: https://techpros.io/ Upcoming Events and Roundtables: https://techpros.io/virtual-experiences/ Join our budding podcast community on LinkedIn: https://www.linkedin.com/company/enterprise-thought-leadership/

Software development is experiencing substantial changes as AI tools alter how teams build, test, and deploy applications. Kyle Hauptfleisch, Chief Growth Officer at Daemon, explores how organisations can successfully navigate these changes without losing the human element that makes great software possible.Kyle brings extensive experience across technology publishing, advertising, core banking, and now leads digital change initiatives at a boutique consultancy. He explains why the current discourse around AI in development divides experienced engineers, and shares practical insights from Daemon's AI-first squad approach.The conversation covers:• Why AI should augment rather than replace human decision-making in software development• The essential role of stakeholder engagement in AI adoption projects• How AI can improve the entire software development lifecycle from requirements gathering through to documentation• The motorcycle versus bicycle analogy: why using AI requires changing how you work• Moving from orchestra member to conductor: the shift in engineering roles• Performance metrics that demonstrate real progress: lead time from whiteboard to production• Daemon's AI-first squad methodology and how it works with client teams• Three practical steps technology leaders can take to embrace AI-first engineeringKyle addresses the tension between developers who see AI as creativity-killing automation and those embracing the acceleration it provides. He argues that engineering stops when coding starts - highlighting how AI can handle the production work whilst humans focus on problem-solving and design.Timestamps: 02:23 Kyle's background and journey to Daemon 03:28 What Daemon does as a digital and AI consultancy 04:38 The current state of AI adoption in software development 07:25 Framework for AI adoption: strategy, data, culture, and applications 09:31 Stakeholder engagement challenges and solutions 11:32 AI-first squads: the core proposition and methodology 12:07 Performance metrics and measuring success 13:18 How AI helps across the software development lifecycle 14:19 Medical organisation case study: turning data into information 14:30 AI in coding: solving problems that have been solved before 18:10 Documentation and unexpected use cases like case study generation 20:32 The motorcycle versus bicycle analogy 21:26 Deploying AI-first squads versus changing engineering capability 25:58 Three actions for technology leaders to embrace AI-first engineeringWant to learn more? Visit Daemon's website: ⁠http://dae.mn ⁠Connect with Kyle Hauptfleisch on LinkedIn: ⁠https://www.linkedin.com/in/kyle-hauptfleisch-84ba2357/ ⁠Connect with Tim Bond: ⁠https://www.linkedin.com/in/tngbond/⁠Email ⁠tim.b@techpros.io⁠If you like our podcast, please follow us and rate each episode. Do you have burning topics or questions you'd like us to explore on the podcast? Email our team at ⁠podcasts@techpros.io.⁠Find out more about TechPros.io: ⁠https://techpros.io/⁠Upcoming Events and Roundtables: ⁠https://techpros.io/virtual-experiences/⁠Join our budding podcast community on LinkedIn: ⁠https://www.linkedin.com/company/enterprise-thought-leadership/

Tim Bond explores the substantial shift happening in graduate employment as companies increasingly prioritise "AI natives" over traditional degree holders. This episode examines how the conventional university-to-job pipeline is fracturing and what this means for students, parents, and educators navigating an uncertain future.Using insights from leading experts including Sam Altman from OpenAI, alongside research from McKinsey, the World Economic Forum, Microsoft, and LinkedIn, this episode unpacks the emergence of "AI-first hiring" and its implications for the next generation entering the workforce.Key topics covered:• Why 66% of business leaders won't hire candidates without AI skills• The "chasm challenge" - the dangerous gap between job displacement and job creation• How major consulting firms like McKinsey are reducing their graduate intake• The decline in confidence in higher education • Alternative pathways emerging beyond traditional degrees• Essential skills for succeeding in an AI-augmented workplace• Practical strategies for future-proofing your careerThe episode reveals both concerning realities and also opportunities for those who understand and adapt to these changes. From the rise of apprenticeships at companies like IBM and Microsoft to the growing importance of hybrid skills that combine AI fluency with uniquely human capabilities, this episode provides a roadmap for navigating the changing employment landscape.Timestamps:• 02:09 The emergence of AI-first hiring practices• 04:00 Data on employer preferences for AI skills• 06:00 New job categories and roles being created• 07:00 Understanding the "chasm challenge"• 09:00 Adapting to exponential change• 11:00 The education system's struggle to keep pace• 13:00 Alternative pathways to traditional education• 17:00 Essential skills for the AI-augmented workplace• 20:00 Seven-step roadmap for career future-proofing• 24:00 Final thoughts and call for perspectivesWant to learn more? Listen to the AI Daily Brief - 20 New jobs AI might create - https://open.spotify.com/episode/3IubJxqwd3ZF9KSuHs8mw0Connect with Tim Bond: https://www.linkedin.com/in/tngbond/If you like our podcast, please follow us and rate each episode. Do you have burning topics or questions you'd like us to explore on the podcast? Email our team at podcasts@techpros.ioFind out more about TechPros.io: https://techpros.io/ Upcoming events and roundtables: https://techpros.io/virtual-experiences/ Follow us on LinkedIn: https://www.linkedin.com/company/enterprise-thought-leadership/